Method and system for real-time measurement of campaign effectiveness

ABSTRACT

A method for real-time measurement of campaign effectiveness includes: storing device profiles, each including a hashed device identifier, geographic location, and transaction entries including a transaction date and transaction data; receiving a data request including a start date, end date, merchant identifier, a plurality of device identifiers, and, for each device identifier, a category identifier of a set of category identifiers; generating a hashed identifier for each of the device identifiers; identifying, a device profile for each hashed device identifier; calculating purchase behaviors for each category based on transaction data in transaction data entries that include a transaction date between the start date and end date that are included in each identified device profile that is associated with the respective category and includes a geographic location corresponding to the merchant identifier; and transmitting at least one of: the calculated purchase behaviors and one or more metrics based thereon.

FIELD

The present disclosure relates to the real-time measurement ofeffectiveness of a campaign, specifically the correlation of transactiondata to computing devices associated therewith for use in determiningcampaign effectiveness for a campaign exposed to known computingdevices, and where identification of the computing devices may beobscured as to provide protection against user privacy andidentification of the computing devices.

BACKGROUND

Determining the effectiveness of a marketing campaign can present anumber of difficulties, particularly with the widespread use of variouscommunication technologies by consumers. Traditionally, paper or otherphysical advertisements were sent or otherwise displayed to consumers,with effectiveness only being measured generally by overall changes inspending on the related products or at the related merchant. With therise of the Internet and other computing devices, the effectiveness ofan advertisement is often determined based on the number of users thatinteract with that advertisement, and, in some instances, the amount ofusers that continue on to make a related purchase if such data isavailable.

However, such methods are only effective in instances where a consumeruses the same avenue for purchase as the avenue used to present theadvertisement to the consumer. As a result, traditional methods may beineffective for measuring the effectiveness for an advertisementcampaign when the use of a mixture of computing device and physicalexposure or transaction occurs, or when a consumer uses multiplecomputing devices. For example, a consumer may be exposed to anadvertisement on a mobile computing device, but may elect to make acorresponding purchase at a physical storefront without use of themobile device. In another example, a consumer may browse the Internet ona smart phone and seen advertisement for a product, but may move to adesktop computer to actually make the purchase. In each instance, thereis a disconnect between the distribution of the advertisement to theconsumer, and the consumer's purchase that prohibits the correlation ofthe purchase to the advertisement, and, therefore, measurement of theeffectiveness of the advertisement based on the technology being used.

Thus, there is a need for a technical solution for the development of atechnological system that can measure the effectiveness of anadvertisement campaign that is distributed to a plurality of computingdevices, where the measurement is not tied to actions taken using thecomputing devices themselves, to account for a wide array of actionsthat may involve the computing devices as well as additional avenues ofpurchase.

SUMMARY

The present disclosure provides a description of systems and methods forthe real-time measurement of campaign effectiveness. As discussedherein, embodiments for the real-time measurement of campaigneffectiveness utilize associations between computing devices andgeographic locations, and the associations of processed transactions tocomputing devices based on geographic location and other factors, todetermine the effectiveness of an advertising campaign based ontransactions occurring in a geographic area.

A method for real-time measurement of campaign effectiveness includes:storing, in a device database of a processing server, a plurality ofdevice profiles, wherein each device profile includes a structured dataset related to a computing device including at least a hashed deviceidentifier, an associated geographic location, and a plurality oftransaction data entries, each transaction data entry including datarelated to a payment transaction including at least a transaction dateand transaction data; receiving, by a receiving device of the processingserver, a data signal superimposed with a data file from a computingsystem, wherein the data file includes data related to a campaignincluding at least, a start date, an end date, at least one merchantidentifier, a plurality of device identifiers, and, for each deviceidentifier, a category identifier of a set of category identifiers;generating, by a hashing module of the processing server, a hashedidentifier for each of the plurality of device identifiers included viaapplication of a hashing algorithm to the respective device identifier;executing, by a querying module of the processing server, a query on thedevice database to identify, for each of the plurality of deviceidentifiers, a corresponding device profile where the included hasheddevice identifier corresponds to the hashed identifier generated for therespective device identifier; calculating, by a calculation module ofthe processing server, at least one purchase behavior for each categoryidentifier of the set of category identifiers for each of the at leastone merchant identifiers, wherein each purchase behavior is based on atleast the transaction data stored in one or more transaction dataentries that include a transaction date between the start date and enddate that are included in each corresponding device profile identifiedfor device identifiers of the plurality of device identifiers where thedevice identifier is associated with the respective category identifierand where the corresponding device profile includes an associatedgeographic location corresponding to the respective merchant identifier;and electronically transmitting, by a transmitting device of theprocessing server, a data signal superimposed with a response data fileto the computing system, wherein the response data file includes atleast one of: the at least one purchase behavior calculated for eachcategory identifier for each of the at least one merchant identifiers,and one or more metrics based on the at least one purchase behaviorcalculated for each category identifier for each of the at least onemerchant identifiers.

A system for real-time measurement of campaign effectiveness includes: adevice database of a processing server configured to store a pluralityof device profiles, wherein each device profile includes a structureddata set related to a computing device including at least a hasheddevice identifier, an associated geographic location, and a plurality oftransaction data entries, each transaction data entry including datarelated to a payment transaction including at least a transaction dateand transaction data; a receiving device of the processing serverconfigured to receive a data signal superimposed with a data file from acomputing system, wherein the data file includes data related to acampaign including at least, a start date, an end date, at least onemerchant identifier, a plurality of device identifiers, and, for eachdevice identifier, a category identifier of a set of categoryidentifiers; a hashing module of the processing server configured togenerate a hashed identifier for each of the plurality of deviceidentifiers included via application of a hashing algorithm to therespective device identifier; a querying module of the processing serverconfigured to execute a query on the device database to identify, foreach of the plurality of device identifiers, a corresponding deviceprofile where the included hashed device identifier corresponds to thehashed identifier generated for the respective device identifier; acalculation module of the processing server configured to calculate atleast one purchase behavior for each category identifier of the set ofcategory identifiers for each of the at least one merchant identifiers,wherein each purchase behavior is based on at least the transaction datastored in one or more transaction data entries that include atransaction date between the start date and end date that are includedin each corresponding device profile identified for device identifiersof the plurality of device identifiers where the device identifier isassociated with the respective category identifier and where thecorresponding device profile includes an associated geographic locationcorresponding to the respective merchant identifier; and a transmittingdevice of the processing server configured to electronically transmit adata signal superimposed with a response data file to the computingsystem, wherein the response data file includes at least one of: the atleast one purchase behavior calculated for each category identifier foreach of the at least one merchant identifiers, and one or more metricsbased on the at least one purchase behavior calculated for each categoryidentifier for each of the at least one merchant identifiers.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

The scope of the present disclosure is best understood from thefollowing detailed description of exemplary embodiments when read inconjunction with the accompanying drawings. Included in the drawings arethe following figures:

FIG. 1 is a block diagram illustrating a high level system architecturefor the real-time measurement of campaign effectiveness in accordancewith exemplary embodiments.

FIG. 2 is a block diagram illustrating the processing server of FIG. 1for the real-time measurement of campaign effectiveness based ongeographic location and transaction data in accordance with exemplaryembodiments.

FIG. 3 is a flow diagram illustrating a process for the real-timemeasurement of the effectiveness of an advertising campaign using thesystem of FIG. 1 in accordance with exemplary embodiments.

FIG. 4 is a flow chart illustrating an exemplary method for real-timemeasurement of campaign effectiveness in accordance with exemplaryembodiments.

FIG. 5 is a flow diagram illustrating the processing of a paymenttransaction in accordance with exemplary embodiments.

FIG. 6 is a block diagram illustrating a computer system architecture inaccordance with exemplary embodiments.

Further areas of applicability of the present disclosure will becomeapparent from the detailed description provided hereinafter. It shouldbe understood that the detailed description of exemplary embodiments areintended for illustration purposes only and are, therefore, not intendedto necessarily limit the scope of the disclosure.

DETAILED DESCRIPTION Glossary of Terms

Payment Network—A system or network used for the transfer of money viathe use of cash-substitutes for thousands, millions, and even billionsof transactions during a given period. Payment networks may use avariety of different protocols and procedures in order to process thetransfer of money for various types of transactions. Transactions thatmay be performed via a payment network may include product or servicepurchases, credit purchases, debit transactions, fund transfers, accountwithdrawals, etc. Payment networks may be configured to performtransactions via cash-substitutes, which may include payment cards,letters of credit, checks, transaction accounts, etc. Examples ofnetworks or systems configured to perform as payment networks includethose operated by MasterCard®, VISA®, Discover®, American Express®,PayPal®, etc. Use of the term “payment network” herein may refer to boththe payment network as an entity, and the physical payment network, suchas the equipment, hardware, and software comprising the payment network.

Payment Rails—Infrastructure associated with a payment network used inthe processing of payment transactions and the communication oftransaction messages and other similar data between the payment networkand other entities interconnected with the payment network that handlesthousands, millions, and even billions of transactions during a givenperiod. The payment rails may be comprised of the hardware used toestablish the payment network and the interconnections between thepayment network and other associated entities, such as financialinstitutions, gateway processors, etc. In some instances, payment railsmay also be affected by software, such as via special programming of thecommunication hardware and devices that comprise the payment rails. Forexample, the payment rails may include specifically configured computingdevices that are specially configured for the routing of transactionmessages, which may be specially formatted data messages that areelectronically transmitted via the payment rails, as discussed in moredetail below.

Transaction Account—A financial account that may be used to fund atransaction, such as a checking account, savings account, creditaccount, virtual payment account, etc. A transaction account may beassociated with a consumer, which may be any suitable type of entityassociated with a payment account, which may include a person, family,company, corporation, governmental entity, etc. In some instances, atransaction account may be virtual, such as those accounts operated byPayPal®, etc.

Merchant—An entity that provides products (e.g., goods and/or services)for purchase by another entity, such as a consumer or another merchant.A merchant may be a consumer, a retailer, a wholesaler, a manufacturer,or any other type of entity that may provide products for purchase aswill be apparent to persons having skill in the relevant art. In someinstances, a merchant may have special knowledge in the goods and/orservices provided for purchase. In other instances, a merchant may nothave or require any special knowledge in offered products. In someembodiments, an entity involved in a single transaction may beconsidered a merchant. In some instances, as used herein, the term“merchant” may refer to an apparatus or device of a merchant entity.

System for Real-Time Measurement of Campaign Effectiveness

FIG. 1 illustrates a system 100 for the real-time measurement of theeffectiveness of an advertising campaign based on geographic locationand transaction data, including the correlation of transaction data tocomputing devices.

The system 100 may include a processing server 102. The processingserver 102, discussed in more detail below, may be configured to providereal-time measurements of the effectiveness of an advertising campaignin a geographic location based on purchase behaviors identified fortransaction data, where the transaction data may associated with paymenttransactions that are tied to computing devices in the same geographiclocation. The processing server 102 may receive a data signalelectronically transmitted by a requesting entity system 104 that issuperimposed or otherwise encoded with a campaign measurement request.The data signal may be electronically transmitted to the processingserver 102 using any suitable communication network and method, such asa local area network, wireless area network, radio frequency network,cellular communication network, or the Internet.

The campaign measurement request may be supplied by the requestingentity system 104, which may be a computing system associated with arequesting entity, which may be any entity that may request measurementsrelated to the effectiveness of an advertising or other distributedcampaign. For example, the requesting entity may be an advertisingagency, research firm, product developer, retailer, etc. The campaignmeasurement request may include at least a start date and end date forthe campaign, a merchant identifier associated with the campaign, and aplurality of device identifiers. The merchant identifier may be anyvalue associated with the campaign that may be directly associated witha merchant or associated with a product or other item associated with amerchant. For example, the merchant identifier may be a merchant name,merchant category code, product identifier, or geographic location.

The device identifiers may be unique values associated with computingdevices 106. Computing devices 106 may be any type of computing devicesuitable for receiving the advertisements or other content distributedby the requesting entity system 104 or an entity associated therewith(e.g., the requesting entity may be separate from the entitydistributing the content), such as a desktop computer, laptop computer,notebook computer, tablet computer, cellular phone, smart phone, smartwatch, smart television, wearable computing device, implantablecomputing device, etc. Device identifiers may be unique valuesassociated therewith suitable for use in the identification thereof,which may include, for example, media access control addresses, internetprotocol addresses, telephone numbers, usernames, e-mail addresses,registration numbers, serial numbers, identification numbers, etc.

In some embodiments, the campaign measurement request may also include,for each of the device identifiers, a category identifier out of a setof category identifiers. Each category identifier may be associated witha category to which the corresponding device identifier is applicable.Category identifiers may be associated with, for example, a test groupand a control group, a control group and groups exposed to one of threedifferent advertisements, etc. In some instances, category identifiersmay be a generic value where such an association is not known to theprocessing server 102. For example, the category identifiers associatedwith device identifiers included in the campaign measurement request maybe values 1, 2, and 3, with their associations not provided to theprocessing server 102 but known to the requesting entity system 104.

The processing server 102 may receive the campaign measurement request,and may generate a hashed identifier corresponding to each of the deviceidentifiers. The hashed identifier may be generated via the applicationof one or more hashing algorithms to a device identifier, which maygenerate the corresponding hashed identifier. In some embodiments, theprocessing server 102 may hash the device identifiers upon receipt suchthat the device identifiers are not retained. In such embodiments, theprocessing server 102 may use hashing algorithms known to the requestingentity system 104. In some cases, the requesting entity system 104 mayinclude hashed device identifiers in the campaign measurement request,such that the identifiers received by the processing server 102 may notbe identifiable of any specific computing device 106.

The processing server 102 may be configured to measure the effectivenessof the campaign indicated in the campaign measurement request inreal-time. The measurement of effectiveness in real-time may refer toherein as the immediate or near immediate initiation of the processes ofthe processing server 102 discussed herein to measure the effectivenessof the campaign using updated data, as opposed to batch processing orthe measurement of effectiveness using historical data. The measurementof the effectiveness of the campaign may be based on purchase behaviorsthat are associated with each category identifier included in the set ofcategory identifiers, as provided in the campaign measurement request.

In the system 100, a plurality of consumers 108 may be associated withvarious computing devices 106, which may include computing devices 106whose corresponding device identifiers are included in the campaignmeasurement request. Each consumer 108 may conduct payment transactionswith one or more merchants 110 using the computing devices 106. Eachpayment transaction involving a consumer 108 and a merchant 110 may beprocessed via a payment network 112. The processing of paymenttransactions by a payment network 112 may include the receipt of atransaction message related to the payment transaction via payment railsassociated with the payment network 112 from a merchant 110 or an entityassociated therewith, such as an acquiring financial institution orgateway processor. Transaction messages may be specially formatted datamessage formatted pursuant to one or more standards governing theexchange of financial transaction messages, such as the InternationalOrganization of Standardization's ISO 8583 or 20022 standards.Transaction messages may include a plurality of data elements configuredto store data associated therewith, such as data elements configured tostore transaction amounts, transaction times, transaction dates,geographic locations, merchant data, product data, offer data, loyaltydata, reward data, point of sale data, issuer data, acquirer data, etc.The exchange of transaction messages and processing of paymenttransactions therewith is discussed in more detail below with respect tothe process 500 illustrated in FIG. 5.

The payment network 112 may electronically transmit transaction data tothe processing server 102 for use in the methods and systems discussedherein. In some embodiments, the payment network 112 may electronicallytransmit transaction messages for processed payment transactions to theprocessing server 102, which may be electronically transmitted viapayment rails associated with the payment network 112 or any othersuitable communication network and method. In other embodiments, thepayment network 112 may electronically transmit the transaction data viaother data messages, which may be formatted in alternative, suitableformats. In some cases, the processing server 102 may be a part of thepayment network 112 and may receive the transaction data via internalcommunication networks and methods, and may also be received as part ofthe processing of the related payment transactions. In some embodiments,transaction data may be provided to the processing server 102 inreal-time or near real-time, such that campaign effectivenessmeasurements provided by the processing server 102 are up to date withrespect to conducted payment transactions.

Transaction data received from the payment network 112 may include, foreach payment transaction, at least a transaction date and additionaltransaction data, such as a transaction amount, transaction time,merchant category code, geographic location, merchant identificationnumber, merchant name, product data, etc. The transaction data for eachpayment transaction may also include an account identifier. The accountidentifier may be an identification value associated with thetransaction account used to fund the payment transaction. The accountidentifier may be a primary account number, or may be a value associatedtherewith that may not be identifiable of the account number by theprocessing server 102, such as a hash value generated via application ofone or more hashing algorithms to the account number or a tokenizedvalue corresponding to the account number. In such instances, thetokenization or hashing may be performed by the processing server 102upon receipt of the transaction data, or may be performed by the paymentnetwork 112 prior to the forwarding of the transaction data.

The transaction data for a payment transaction may also include a deviceidentifier. The device identifier may be associated with the computingdevice 106 used to initiate the payment transaction, which may becaptured as part of the traditional methods for processing paymenttransactions involving computing devices. In some embodiments, thepayment network 112 and/or processing server 102 may be configured tohash the device identifier such that the transaction data provided tothe processing server 102 includes only hashed device identifiers.

The processing server 102 may receive the transaction data and may beconfigured to associate payment transactions with device identifiers andassociated device identifiers with geographic locations. The associationof payment transactions with device identifiers may include identifyingtransaction data for payment transactions that include a deviceidentifier, as well as identifying other payment transactions (e.g.,with no device identifier included) that include the same accountidentifier included in those having the device identifier. Theprocessing server 102 may also be configured to identify a geographiclocation for account identifiers and device identifiers based on thegeographic location included in related payment transactions. Theprocessing server 102 may identify account identifiers and deviceidentifiers that have the same geographic location associated therewithto create a correspondence thereto. The processing server 102 may thenassociate all payment transactions with an account identifier with thecorresponding device identifier, which may thus include the associationof in-person and other payment transactions not conducted via acomputing device 106, or conducted via a different computing device 106.Additional information regarding the identification of a geographiclocation for a transaction account and for a computing device involvedin payment transactions is discussed in more detail in U.S. ProvisionalPatent Application No. 62/183,955, entitled “Method and System forEstimating Residence Latitude and Longitude with Transaction Data,”filed on Jun. 24, 2015, by Serge Bernard et al., which is hereinincorporated by reference in its entirety.

For each of the device identifiers included in the campaign measurementrequest, the processing server 102 may identify the transaction datarelated to payment transactions associated therewith. As discussedabove, the transaction data may include payment transactions conductedusing the computing device 106 associated with the device identifier, aswell as other payment transactions associated with the same consumer 108and/or transaction account, which may include payment transactionsconducted without the use of a computing device 106. As a result, themethods and systems discussed herein may enable the processing server102 to measure campaign effectiveness that takes into account multipleavenues for transacting beyond the one used to distribute the campaign.

The processing server 102 may be configured to calculate one or morepurchase behaviors for each category provided in the campaignmeasurement request. The purchase behaviors may be calculated based onthe transaction data for each payment transaction that is associatedwith a device identifier that is associated with the respective categoryidentifier, which may be for payment transactions specific to thecampaign being measured. Such payment transactions may be those withtransaction dates occurring between the start and end dates for thecampaign. In some cases, the payment transactions may include a merchantidentifier corresponding to the merchant identifier included in thecampaign measurement request. In other cases, purchase behaviors mayonly be calculated using transaction data associated with deviceidentifiers that have geographic locations corresponding to the merchantidentifier (e.g., if a geographic location, or a geographic locationassociated with the supplied merchant identifier) included in thecampaign measurement request.

Purchase behaviors may include consumer behaviors associated withpayment transaction that may be identified based on the data associatedtherewith, including the average transaction spend, transactionfrequency, number of transactions, propensity to spend, propensity tospend a specific transaction amount or beyond a specific thresholdamount, etc., and may be identified for one or more criteria associatedwith payment transactions, such the calculation of a purchase behaviorfor a specific geographic location, merchant, product, day of the week,time of day, other criteria, or a combination thereof. For instance, theprocessing server 102 may calculate purchase behaviors for each categorythat includes the average transaction spend, transaction frequency, andnumber of transactions on the whole for each device identifier, as wellas those same three behaviors for each device identifier for themerchant industry identified in the campaign measurement request for aperiod of time before the campaign start date, for the campaign period,for a period of time after the campaign period, and the same purchasebehaviors for a specific merchant identified in the campaign measurementrequest.

The processing server 102 may use the purchase behaviors to identify oneor more metrics for providing to the requesting entity system 104. Theone or more metrics may be based on the purchase behaviors and, in someinstances, may be identified for each category identifier. The metricsmay include the purchase behaviors themselves or summaries thereof andmay include a campaign effectiveness value. The campaign effectivenessvalue may be based on a comparison of the purchase behaviors calculatedfor each of the identified categories. For instance, in the aboveexample, the purchase behaviors may be calculated for a category ofdevice identifiers exposed to the campaign and a control group notexplicitly exposed to the campaign, where the processing server 102 maycalculate a campaign effectiveness value by analyzing the changes inspend and frequency for each device identifier deliberately exposed tothe campaign for the targeted merchant as compared to that merchantindustry in general for each device identifier, as also compared to thesame behaviors for those in the control group. In an example, theprocessing server 102 may identify a high effectiveness value if thepurchase behaviors indicate a large growth in average spend at theparticular merchant that goes beyond the growth for that industry by thedevice identifiers in the test group that is not seen for the deviceidentifiers in the control group.

The processing server 102 may electronically transmit a data signal backto the requesting entity system 104 using the suitable communicationnetwork and method that is superimposed or otherwise encoded with thepurchase behaviors and/or identified metrics, which may include thecampaign effectiveness value. The requesting entity system 104 may thenact accordingly based on the data. For example, if the categoriesinclude test groups for three different advertisements, the requestingentity system 104 may launch a campaign centered on the most effectiveadvertisement.

In some embodiments, the processing server 102 may also incorporatedemographic characteristics in the purchase behavior and metriccalculations. In such embodiments, the processing server 102 may receivedemographic characteristics for consumer 108 from a demographic trackingagency 114. The demographic tracking agency 114 may be configured toidentify demographic characteristics for consumers 108 using suitablemethods, and may associate the demographic characteristics withtransaction accounts. The demographic tracking agency 114 mayelectronically transmit a data signal to the processing server 102 usinga suitable method that is superimposed or otherwise encoded withassociations between transaction accounts (e.g., using account numbersor account identifiers, which may be hashed account numbers generatedusing the same hashing algorithm as the processing server 102) anddemographic characteristics. The demographic characteristics mayinclude, for example, gender, age, income, occupation, education,residential status, marital status, familial status, etc.

In such embodiments, the processing server 102 may calculate purchasebehaviors for each combination of category and demographiccharacteristic. In some such embodiments, the requesting entity system104 may indicate in the campaign measurement request the demographiccharacteristics to use. In some instances, the categories themselves maybe demographic characteristics or may incorporate demographiccharacteristics. For example, the campaign measurement request mayinclude category identifiers and associated device identifiers for amale test audience, a female test audience, a male control audience, anda female control audience. In some instances, the device identifiers maynot be associated with demographic characteristics in the campaignmeasurement request, but may be associated therewith by the processingserver 102 based on the data received from the demographic trackingagency 114. For example, the requesting entity system 104 may providedevice identifiers for test and control audiences, and may requestseparation by gender, which may be performed by the processing server102. In such instances, the requesting entity system 104 may receivedemographic-specific information, without the need to gather demographicdata by use of the processing server 102.

The methods and systems discussed herein enable the processing server102 to measure the effectiveness of a campaign in real-time or nearreal-time, which takes into account all payment transactions associatedwith a computing device 106, including payment transactions notconducted directly with that computing device 106, which may beconducted via an alternative computing device 106 or an entirelydifferent payment method. As a result, the measurements provided by theprocessing server 102 using the technological system discussed hereinmay be more accurate, and thus more effective and valuable, than thoseprovided in traditional systems. In addition, the use of demographiccharacteristics may further enhance the value of the metrics andmeasurements provided by the processing server 102 using the methods andsystems discussed herein.

Processing Server

FIG. 2 illustrates an embodiment of a processing server 102 of theprocessing system 102 in the system 100. It will be apparent to personshaving skill in the relevant art that the embodiment of the processingserver 102 illustrated in FIG. 2 is provided as illustration only andmay not be exhaustive to all possible configurations of the computingsystems 200 of the processing system 102 suitable for performing thefunctions as discussed herein. For example, the computer system 600illustrated in FIG. 6 and discussed in more detail below may be asuitable configuration of the processing server 102.

The processing server 102 may include a receiving device 202. Thereceiving device 202 may be configured to receive data over one or morenetworks via one or more network protocols. In some embodiments, thereceiving device 202 may be configured to receive data over the paymentrails, such as using specially configured infrastructure associated withpayment networks 112 for the transmission of transaction messages thatinclude sensitive financial data and information. In some instances, thereceiving device 202 may also be configured to receive data fromrequesting entity systems 104, payment networks 112, demographictracking agencies 114, and other entities via alternative networks, suchas the Internet. In some embodiments, the receiving device 202 may becomprised of multiple devices, such as different receiving devices forreceiving data over different networks, such as a first receiving devicefor receiving data over payment rails and a second receiving device forreceiving data over the Internet. The receiving device 202 may receiveelectronically transmitted data signals, where data may be superimposedor otherwise encoded on the data signal and decoded, parsed, read, orotherwise obtained via receipt of the data signal by the receivingdevice 202. In some instances, the receiving device 202 may include aparsing module for parsing the received data signal to obtain the datasuperimposed thereon. For example, the receiving device 202 may includea parser program configured to receive and transform the received datasignal into usable input for the functions performed by the processingdevice to carry out the methods and systems described herein.

The receiving device 202 may be configured to receive data signalselectronically transmitted by payment networks 112 via payment railsassociated therewith that may be superimposed or otherwise encoded withtransaction messages. Transaction messages may be formatted pursuant toone or more standards, such as the ISO 8583 or 20022 standards, andinclude a message type indicator and a plurality of data elements, suchas data elements configured to store primary account numbers,transaction amounts, merchant identifiers, transaction times and/ordates, device identifiers, and additional transaction data. In someinstances, transaction data may be formatted in alternative datamessages, which may be received via the payment rails associated withthe payment network 112 or a suitable alternative communication network.The receiving device 202 may also be configured to receive data signalselectronically transmitted by requesting entity systems 104, which maybe superimposed or otherwise encoded with campaign measurement requests.Campaign measurement requests may include at least a start date, an enddate, a merchant identifier, a plurality of device identifiers, and, foreach device identifier an associated category identifier for one of agroup of categories. In some embodiments, the receiving device 202 mayalso be configured to receive data signals electronically transmitted bydemographic tracking agencies 114, which may be superimposed orotherwise encoded with associations between demographic characteristicsand account numbers or identifiers.

The processing server 102 may also include a communication module 204.The communication module 204 may be configured to transmit data betweenmodules, engines, databases, memories, and other components of theprocessing server 102 for use in performing the functions discussedherein. The communication module 204 may be comprised of one or morecommunication types and utilize various communication methods forcommunications within a computing device. For example, the communicationmodule 204 may be comprised of a bus, contact pin connectors, wires,etc. In some embodiments, the communication module 204 may also beconfigured to communicate between internal components of the processingserver 102 and external components of the processing server 102, such asexternally connected databases, display devices, input devices, etc. Theprocessing server 102 may also include a processing device. Theprocessing device may be configured to perform the functions of theprocessing server 102 discussed herein as will be apparent to personshaving skill in the relevant art. In some embodiments, the processingdevice may include and/or be comprised of a plurality of engines and/ormodules specially configured to perform one or more functions of theprocessing device, such as a querying module 214, hashing module 216,calculation module 218, etc. As used herein, the term “module” may besoftware or hardware particularly programmed to receive an input,perform one or more processes using the input, and provide an output.The input, output, and processes performed by various modules will beapparent to one skilled in the art based upon the present disclosure.

The processing server 102 may include a device database 206. The devicedatabase 206 may be configured to store a plurality of device profiles208 using a suitable data storage format and schema. The device database206 may be a relational database that utilizes structured query languagefor the storage, identification, modifying, updating, accessing, etc. ofstructured data sets stored therein. Each device profile 208 may be astructured data set configured to store data related to a computingdevice 106. Each device profile 208 may include at least a hashed deviceidentifier associated with the related computing device, a geographiclocation associated therewith, and a plurality of transaction dataentries. Each transaction data entry may be related to a paymenttransaction associated with the related computing device and include atleast a transaction date and additional transaction data. In someembodiments, each transaction data entry may be a transaction messageformatted pursuant to one or more standards, such as the ISO 8583 or20022 standards. In some instances, a device profile 208 may alsoinclude a plurality of demographic characteristics associated therewith.

In some embodiments, the processing server 102 may also include amerchant database 210. The merchant database 210 may be configured tostore a plurality of merchant profiles 212 using a suitable data storageformat and schema. The merchant database 210 may be a relationaldatabase that utilizes structured query language for the storage,identification, modifying, updating, accessing, etc. of structured datasets stored therein. Each merchant profile 212 may be a structured dataset configured to store data related to one or more merchants 110. Eachmerchant profile 212 may include at least a merchant identifier and anassociated merchant geographic location. In such embodiments, themerchant identifier included in a campaign measurement request (e.g.,received via the receiving device 202) may not be a geographic location.In such embodiments, the merchant identifier may be a unique valueassociated with a specific merchant 110 or merchant industry, such as amerchant identification number, merchant category code, etc.

The processing server 102 may include a querying module 214. Thequerying module 214 may be configured to execute queries on databases toidentify information. The querying module 214 may receive one or moredata values or query strings, and may execute a query string basedthereon on an indicated database, such as the device database 206, toidentify information stored therein. The querying module 214 may thenoutput the identified information to an appropriate engine or module ofthe processing server 102 as necessary. The querying module 214 may, forexample, execute a query on the device database 206 to identify a deviceprofile 208 for each hashed device identifier included in a receivedcampaign measurement request. In another example, the querying module214 may execute a query on the merchant database 210 to identify amerchant profile 212 that includes a merchant identifier included in areceived campaign measurement request.

The processing server 102 may also include a hashing module 216. Thehashing module 216 may be configured to generate hash values for use inperforming the functions of the processing server 102 as discussedherein. Hash values may be generated via the application of one or morehashing algorithms to data. The hashing module 216 may receive data tobe hashed as input, may generate a hash value via hashing of the data,and may output the resulting hash value to another module or engine ofthe processing server 102. In some instances, the input may also includethe one or more hashing algorithms to be used by the hashing module 216,or the hashing module 216 may be configured to identify the one or morehashing algorithms to use. The hashing module 216 may be configured to,for example, hash device identifiers and account numbers received by thereceiving device 202 upon receipt such that the underlying deviceidentifiers and account numbers are not possessed by the processingserver 102.

The processing server 102 may also include a calculation module 218. Thecalculation module 218 may be configured to calculate purchase behaviorsand metrics based on transaction data. The calculation module 218 mayreceive a plurality of transaction data entries and one or morerequested purchase behaviors and/or metrics as input, may calculate therequested purchase behaviors and/or metrics based on transaction dataincluded in each transaction data entry related thereto, and may outputthe results to another module or engine of the processing server 102.For example, the calculation module 218 may receive a plurality oftransaction data entries associated with a specific category identifierand set of demographic characteristics (e.g., as identified via thequerying module 214) as well as a metric for calculation (e.g., such asmay be requested in the campaign measurement request), and may calculatethe requested metric based on the transaction data included in thetransaction data entries, and may output the requested metric fortransmission back to the requesting entity system 104.

The processing server 102 may also include a transmitting device 220.The transmitting device 220 may be configured to transmit data over oneor more networks via one or more network protocols. In some embodiments,the transmitting device 220 may be configured to transmit data over thepayment rails, such as using specially configured infrastructureassociated with payment networks 112 for the transmission of transactionmessages that include sensitive financial data and information, such asidentified payment credentials. In some instances, the transmittingdevice 220 may be configured to transmit data to requesting entitysystems 104, payment networks 112, demographic tracking agencies 114,and other entities via alternative networks, such as the Internet. Insome embodiments, the transmitting device 220 may be comprised ofmultiple devices, such as different transmitting devices fortransmitting data over different networks, such as a first transmittingdevice for transmitting data over the payment rails and a secondtransmitting device for transmitting data over the Internet. Thetransmitting device 220 may electronically transmit data signals thathave data superimposed that may be parsed by a receiving computingdevice. In some instances, the transmitting device 220 may include oneor more modules for superimposing, encoding, or otherwise formattingdata into data signals suitable for transmission.

The transmitting device 220 may be configured to electronically transmitdata signals to requesting entity systems 104 that are superimposed orotherwise encoded with calculated purchase behaviors and/or metrics. Thetransmitting device 220 may also be configured to electronicallytransmit data signals superimposed or otherwise encoded with datarequests, such as may be transmitted to the payment network 112 (e.g.,requesting transaction data for specific transaction accounts and/ordevice identifiers) or the demographic tracking agency 114 (e.g.,requesting demographic characteristics for specific transactionaccounts).

The processing server 102 may also include a memory 222. The memory 222may be configured to store data for use by the processing server 102 inperforming the functions discussed herein. The memory 222 may beconfigured to store data using suitable data formatting methods andschema and may be any suitable type of memory, such as read-only memory,random access memory, etc. The memory 222 may include, for example,encryption keys and algorithms, communication protocols and standards,data formatting standards and protocols, program code for modules andapplication programs of the processing device, and other data that maybe suitable for use by the processing server 102 in the performance ofthe functions disclosed herein as will be apparent to persons havingskill in the relevant art. In some embodiments, the memory 222 may becomprised of or may otherwise include a relational database thatutilizes structured query language for the storage, identification,modifying, updating, accessing, etc. of structured data sets storedtherein.

Process for Real-Time Measurement of Campaign Effectiveness

FIG. 3 illustrates a process 300 for the real-time measurement of theeffectiveness of a campaign based on purchase behaviors associated withcomputing devices 106 that takes into account payment transactions notdirectly associated with each computing device 106.

In step 302, the receiving device 202 of the processing server 102 mayreceive transaction data for a plurality of payment transactions. Thetransaction data may be included in transaction data entries ortransaction messages electronically transmitted by one or more paymentnetworks 112. The transaction data for each payment transaction may beassociated with a hashed device identifier and include at least atransaction date and additional transaction data. The association with adevice identifier may be indicated in the transmission from the paymentnetwork 112, or may be identified by the processing server 102 usingmethods and systems that will be apparent to persons having skill in therelevant art. The additional transaction data may include a transactionamount, geographic location, transaction time, merchant identifier,merchant data, point of sale data, product data, offer data, loyaltydata, reward data, issuer data, acquirer data, etc. The querying module214 of the processing server 102 may execute one or more queries on thedevice database 206 to store the received transaction data in deviceprofiles 208 that include the respective hashed device identifier.

In step 304, the requesting entity system 104 or an entity associatedtherewith my run an advertising campaign. The advertising campaign mayinclude the distribution of advertisements to a plurality of computingdevices 106 for which the associated device identifiers are known, andmay also include the identification of computing devices 106 that arenot deliberately exposed to the advertisements. The requesting entitysystem 104 may identify a plurality of different categories of computingdevices 106 involved in the campaign. In step 306, the requesting entitysystem 104 may generate a request data file to request a measurement ofeffectiveness of the campaign. The request data file may include each ofthe device identifiers associated with the computing devices 106involved in the campaign and, for each device identifier, a categoryidentifier associated with one of a plurality of categories, and mayalso include a start and end date for the campaign, and a merchantidentifier associated with a target of the campaign. The merchantidentifier may be, for example, a geographic location, a merchantidentification number, or a merchant category code. In some embodiments,the request may also indicate one or more purchase behaviors and/ormetrics that are requested.

In step 308, the requesting entity system 104 may electronicallytransmit a data signal to the processing server 102 that is superimposedor otherwise encoded with the generated request data file to request themeasurement of campaign effectiveness. The data signal may beelectronically transmitted using any suitable communication network andmethod and, in step 310, may be received by the receiving device 202 ofthe processing server 102. In step 312, the hashing module 216 of theprocessing server 102 may hash each of the device identifiers includedin the request data file via the application of one or more hashingalgorithms thereto. In some embodiments, step 312 may be performedduring the receipt of the request data file in step 310 such that theprocessing server 102 does not possess the un-hashed device identifiers.

In step 314, the querying module 214 of the processing server 102 mayexecute a query on the device database 206 of the processing server 102to identify a device profile 208 related to each of the deviceidentifiers included in the request data file, where the device profile208 includes the corresponding hashed identifier. In some embodiments,the processing server 102 may only identify the device profiles 208 thatalso include a geographic location that corresponds to the merchantidentifier included in the request data file. In instances where themerchant identifier may not be a geographic location, the queryingmodule 214 may execute a query on the merchant database 210 to identifya merchant profile 212 that includes the merchant identifier, foridentification of the geographic location stored therein, which may beused for filtering of the device profiles 208.

In step 316, the calculation module 218 of the processing server 102 maycalculate a plurality of purchase behaviors. The purchase behaviors maybe calculated for each category of device identifiers as indicated inthe request data file, and, if applicable, may be further specific tocombinations of categories and demographic characteristics. The purchasebehaviors for each category may be calculated based on the transactiondata included in one of more of the transaction data entries stored inone or more of the identified device profiles 208 where thecorresponding device identifier is associated with the respectivecategory identifier. In instances where demographic characteristics areused, the transaction data entries may be include in device profiles 208that include the respective demographic characteristics. In someembodiments, the purchase behaviors may be indicated in the request datafile or based thereon, such as the calculation module 218 calculating aspecific set of purchase behaviors necessary to identify a metricrequested by the requesting entity system 104.

In an example, the requesting entity system 104 may request a campaigneffectiveness value for a campaign targeted towards men between the agesof 25 and 34, with device identifiers for control and test audiencessupplied. The purchase behaviors may thus be identified for test andcontrol audiences broken down by gender and age group, including a testand control audience for men between the ages of 25 and 34, and at leastone test and control audience for all other demographic characteristics,which may also be broken up into one or more gender/age groups. Forinstance, the purchase behaviors may also be calculated for test andcontrol groups of men under 25 and men above 34, and women for each ofthe three age groups. The purchase behaviors calculated in such anexample may include transaction frequency and average spend overall, inthe merchant industry, and at the specific merchant identified in therequest data file. Such purchase behaviors may be based on at least thetransaction amount, merchant category code, and merchant identificationnumber stored in each transaction data entry.

In step 318, the calculation module 218 of the processing server 102 maycalculate a campaign effectiveness value. The campaign effectivenessvalue may be calculated based on a comparison of the purchase behaviorscalculated for each of the groups indicated in the request data file.For instance, in the above example, the calculation module 218 maycompare the spend levels and transaction frequency for the group of menbetween the ages of 25 and 34 to those in each of the other groups, todetermine if any change in spend amount or transaction frequency isunique to men of that age group, that age group specifically, menspecifically, or experienced in both genders and multiple age groups. Insome instances, multiple campaign effectiveness values may be identifiedby the calculation module 218. For instances, in the above example, thecalculation module 218 may determine a high effectiveness in the targetage group, but may also identify that the same age group for women hasalso experience an increase in spend amount and transaction frequency,and may generate an effectiveness value accordingly.

In step 320, the transmitting device 220 of the processing server 102may electronically transmit a data signal to the requesting entitysystem 104 that is superimposed or otherwise encoded with the calculatedcampaign effectiveness value or values, and, if applicable, one or moreof the calculated purchase behaviors. In step 322, the requesting entitysystem 104 may receive the campaign effectiveness value and may performone or more actions accordingly. For instance, in the above example, therequesting entity system 104 may begin to target both men and womenbetween the ages of 25 and 34 with their advertising campaign due to themeasured effectiveness.

Exemplary Method for Real-Time Measurement of Campaign Effectiveness

FIG. 4 illustrates a method 400 for the real-time measurement ofcampaign effectiveness based on computing devices and associatedgeographic locations, and transaction data directly or indirectlyassociated therewith.

In step 402, a plurality of device profiles (e.g., device profiles 208)may be stored in a device database (e.g., the device database 206) of aprocessing server (e.g., the processing server 102), wherein each deviceprofile includes a structured data set related to a computing device(e.g., a computing device 106) including at least a hashed deviceidentifier, an associated geographic location, and a plurality oftransaction data entries, each transaction data entry including datarelated to a payment transaction including at least a transaction dateand transaction data. In step 404, a data signal superimposed with adata file may be received by a receiving device (e.g., the receivingdevice 202) of the processing server from a computing system (e.g., therequesting entity system 104), wherein the data file includes datarelated to a campaign including at least, a start date, an end date, atleast one merchant identifier, a plurality of device identifiers, and,for each device identifier, a category identifier of a set of categoryidentifiers.

In step 406, a hashed identifier may be generated for each of theplurality of device identifiers included in the received data file by ahashing module (e.g., the hashing module 216) of the processing servervia application of one or more hashing algorithms to the respectivedevice identifier. In step 408, a query may be executed by a queryingmodule (e.g., the querying module 214) of the processing server 102 onthe device database to identify, for each of the plurality of deviceidentifiers, a corresponding device profile where the included hasheddevice identifier corresponds to the hashed identifier generated for therespective device identifier.

In step 410, at least one purchase behavior may be calculated by acalculation module (e.g., the calculation module 218) of the processingserver for each category identifier of the set of category identifiersfor each of the at least one merchant identifiers, wherein each purchasebehavior is based on at least the transaction data stored in one or moretransaction data entries that include a transaction date between thestart date and end date that are included in each corresponding deviceprofile identified for device identifiers of the plurality of deviceidentifiers where the device identifier is associated with therespective category identifier and where the corresponding deviceprofile includes an associated geographic location corresponding to therespective merchant identifier. In step 412, a data signal superimposedwith a response data file may be electronically transmitted by atransmitting device (e.g., the transmitting device 220) of theprocessing server to the computing system, wherein the response datafile includes at least one of: the at least one purchase behaviorcalculated for each category identifier for each of the at least onemerchant identifiers, and one or more metrics based on the at least onepurchase behavior calculated for each category identifier for each ofthe at least one merchant identifiers.

In one embodiment, the method 400 may further include calculating, bythe calculation module of the processing server, a campaigneffectiveness value for the campaign based on a comparison, for each ofthe at least one merchant identifier, of the at least one purchasebehavior calculated for each category identifier for the respective atleast one merchant identifier, wherein the one or more metrics includesthe calculated campaign effectiveness value. In a further embodiment,the set of category identifiers may include a test group identifier anda control group identifier. In one embodiment, each of the at least onemerchant identifiers may be a geographic location associated with one ormore merchants. In some embodiments, the one or more metrics may includeat least one of: change in average spend, change in total spend, changein transaction frequency, and change in number of transactions.

In one embodiment, the method 400 may also include: storing, in amerchant database (e.g., the merchant database 210) of the processingserver, a plurality of merchant profiles (e.g., merchant profiles 212),wherein each merchant profile includes a structured data set related toa merchant including at least a merchant identifier and a merchantgeographic location; and executing, by the querying module of theprocessing server, a query on the merchant database to identify, foreach of the at least one merchant identifier, a corresponding merchantprofile that includes the respective merchant identifier, wherein thecorrespondence between the associated geographic location included in adevice profile and a merchant identifier is based on a correspondencebetween the associated geographic location and the merchant geographiclocation included in the merchant profile corresponding to therespective merchant identifier. In a further embodiment, the merchantidentifier may be one of: a merchant identification number and amerchant name.

In some embodiments, each account profile may further includes one ormore demographic characteristics of a set of demographiccharacteristics, the at least one purchase behavior calculated for eachcategory identifier of the set of category identifiers for each of theat least one merchant identifiers may be calculated for each demographiccharacteristic of the set of demographic characteristics, and the atleast one purchase behavior may be based on the transaction data storedin one or more transaction data entries included in a correspondingdevice profile where the included one or more demographiccharacteristics include the respective demographic characteristic. In afurther embodiment, the data file may further include the set ofdemographic characteristics. In another further embodiment, the method400 may further include calculating, by the calculation module of theprocessing server, a campaign effectiveness value for the campaign basedon a comparison, for each of the at least one merchant identifier anddemographic characteristic, of the at least one purchase behaviorcalculated for each category identifier for the respective at least onemerchant identifier and demographic characteristic, wherein the one ormore metrics includes the calculated campaign effectiveness value.

Payment Transaction Processing System and Process

FIG. 5 illustrates a transaction processing system and a process 500 forthe processing of payment transactions in the system, which may includethe processing of thousands, millions, or even billions of transactionsduring a given period (e.g., hourly, daily, weekly, etc.). The process500 and steps included therein may be performed by one or morecomponents of the system 100 discussed above, such as the processingserver 102, consumers 108, computing devices 106, merchants 110, paymentnetwork 112, etc. The processing of payment transactions using thesystem and process 500 illustrated in FIG. 5 and discussed below mayutilize the payment rails, which may be comprised of the computingdevices and infrastructure utilized to perform the steps of the process500 as specially configured and programmed by the entities discussedbelow, including the transaction processing server 512, which may beassociated with one or more payment networks configured to processingpayment transactions. It will be apparent to persons having skill in therelevant art that the process 500 may be incorporated into the processesillustrated in FIGS. 3 and 4, discussed above, with respect to the stepor steps involved in the processing of a payment transaction. Inaddition, the entities discussed herein for performing the process 500may include one or more computing devices or systems configured toperform the functions discussed below. For instance, the merchant 506may be comprised of one or more point of sale devices, a localcommunication network, a computing server, and other devices configuredto perform the functions discussed below.

In step 520, an issuing financial institution 502 may issue a paymentcard or other suitable payment instrument to a consumer 504. The issuingfinancial institution may be a financial institution, such as a bank, orother suitable type of entity that administers and manages paymentaccounts and/or payment instruments for use with payment accounts thatcan be used to fund payment transactions. The consumer 504 may have atransaction account with the issuing financial institution 502 for whichthe issued payment card is associated, such that, when used in a paymenttransaction, the payment transaction is funded by the associatedtransaction account. In some embodiments, the payment card may be issuedto the consumer 504 physically. In other embodiments, the payment cardmay be a virtual payment card or otherwise provisioned to the consumer504 in an electronic format.

In step 522, the consumer 504 may present the issued payment card to amerchant 506 for use in funding a payment transaction. The merchant 506may be a business, another consumer, or any entity that may engage in apayment transaction with the consumer 504. The payment card may bepresented by the consumer 504 via providing the physical card to themerchant 506, electronically transmitting (e.g., via near fieldcommunication, wireless transmission, or other suitable electronictransmission type and protocol) payment details for the payment card, orinitiating transmission of payment details to the merchant 506 via athird party. The merchant 506 may receive the payment details (e.g., viathe electronic transmission, via reading them from a physical paymentcard, etc.), which may include at least a transaction account numberassociated with the payment card and/or associated transaction account.In some instances, the payment details may include one or moreapplication cryptograms, which may be used in the processing of thepayment transaction.

In step 524, the merchant 506 may enter transaction details into a pointof sale computing system. The transaction details may include thepayment details provided by the consumer 504 associated with the paymentcard and additional details associated with the transaction, such as atransaction amount, time and/or date, product data, offer data, loyaltydata, reward data, merchant data, consumer data, point of sale data,etc. Transaction details may be entered into the point of sale system ofthe merchant 506 via one or more input devices, such as an optical barcode scanner configured to scan product bar codes, a keyboard configuredto receive product codes input by a user, etc. The merchant point ofsale system may be a specifically configured computing device and/orspecial purpose computing device intended for the purpose of processingelectronic financial transactions and communicating with a paymentnetwork (e.g., via the payment rails). The merchant point of sale systemmay be an electronic device upon which a point of sale systemapplication is run, wherein the application causes the electronic deviceto receive and communicated electronic financial transaction informationto a payment network. In some embodiments, the merchant 506 may be anonline retailer in an e-commerce transaction. In such embodiments, thetransaction details may be entered in a shopping cart or otherrepository for storing transaction data in an electronic transaction aswill be apparent to persons having skill in the relevant art.

In step 526, the merchant 506 may electronically transmit a data signalsuperimposed with transaction data to a gateway processor 508. Thegateway processor 508 may be an entity configured to receive transactiondetails from a merchant 506 for formatting and transmission to anacquiring financial institution 510. In some instances, a gatewayprocessor 508 may be associated with a plurality of merchants 506 and aplurality of acquiring financial institutions 510. In such instances,the gateway processor 508 may receive transaction details for aplurality of different transactions involving various merchants, whichmay be forwarded on to appropriate acquiring financial institutions 510.By having relationships with multiple acquiring financial institutions510 and having the requisite infrastructure to communicate withfinancial institutions using the payment rails, such as usingapplication programming interfaces associated with the gateway processor508 or financial institutions used for the submission, receipt, andretrieval of data, a gateway processor 508 may act as an intermediaryfor a merchant 506 to be able to conduct payment transactions via asingle communication channel and format with the gateway processor 508,without having to maintain relationships with multiple acquiringfinancial institutions 510 and payment processors and the hardwareassociated thereto. Acquiring financial institutions 510 may befinancial institutions, such as banks, or other entities thatadministers and manages payment accounts and/or payment instruments foruse with payment accounts. In some instances, acquiring financialinstitutions 510 may manage transaction accounts for merchants 506. Insome cases, a single financial institution may operate as both anissuing financial institution 502 and an acquiring financial institution510.

The data signal transmitted from the merchant 506 to the gatewayprocessor 508 may be superimposed with the transaction details for thepayment transaction, which may be formatted based on one or morestandards. In some embodiments, the standards may be set forth by thegateway processor 508, which may use a unique, proprietary format forthe transmission of transaction data to/from the gateway processor 508.In other embodiments, a public standard may be used, such as theInternational Organization for Standardization's ISO 8583 standard. Thestandard may indicate the types of data that may be included, theformatting of the data, how the data is to be stored and transmitted,and other criteria for the transmission of the transaction data to thegateway processor 508.

In step 528, the gateway processor 508 may parse the transaction datasignal to obtain the transaction data superimposed thereon and mayformat the transaction data as necessary. The formatting of thetransaction data may be performed by the gateway processor 508 based onthe proprietary standards of the gateway processor 508 or an acquiringfinancial institution 510 associated with the payment transaction. Theproprietary standards may specify the type of data included in thetransaction data and the format for storage and transmission of thedata. The acquiring financial institution 510 may be identified by thegateway processor 508 using the transaction data, such as by parsing thetransaction data (e.g., deconstructing into data elements) to obtain anaccount identifier included therein associated with the acquiringfinancial institution 510. In some instances, the gateway processor 508may then format the transaction data based on the identified acquiringfinancial institution 510, such as to comply with standards offormatting specified by the acquiring financial institution 510. In someembodiments, the identified acquiring financial institution 510 may beassociated with the merchant 506 involved in the payment transaction,and, in some cases, may manage a transaction account associated with themerchant 506.

In step 530, the gateway processor 508 may electronically transmit adata signal superimposed with the formatted transaction data to theidentified acquiring financial institution 510. The acquiring financialinstitution 510 may receive the data signal and parse the signal toobtain the formatted transaction data superimposed thereon. In step 532,the acquiring financial institution may generate an authorizationrequest for the payment transaction based on the formatted transactiondata. The authorization request may be a specially formatted transactionmessage that is formatted pursuant to one or more standards, such as theISO 8583 standard and standards set forth by a payment processor used toprocess the payment transaction, such as a payment network. Theauthorization request may be a transaction message that includes amessage type indicator indicative of an authorization request, which mayindicate that the merchant 506 involved in the payment transaction isrequesting payment or a promise of payment from the issuing financialinstitution 502 for the transaction. The authorization request mayinclude a plurality of data elements, each data element being configuredto store data as set forth in the associated standards, such as forstoring an account number, application cryptogram, transaction amount,issuing financial institution 502 information, etc.

In step 534, the acquiring financial institution 510 may electronicallytransmit the authorization request to a transaction processing server512 for processing. The transaction processing server 512 may becomprised of one or more computing devices as part of a payment networkconfigured to process payment transactions. In some embodiments, theauthorization request may be transmitted by a transaction processor atthe acquiring financial institution 510 or other entity associated withthe acquiring financial institution. The transaction processor may beone or more computing devices that include a plurality of communicationchannels for communication with the transaction processing server 512for the transmission of transaction messages and other data to and fromthe transaction processing server 512. In some embodiments, the paymentnetwork associated with the transaction processing server 512 may own oroperate each transaction processor such that the payment network maymaintain control over the communication of transaction messages to andfrom the transaction processing server 512 for network and informationalsecurity.

In step 536, the transaction processing server 512 may performvalue-added services for the payment transaction. Value-added servicesmay be services specified by the issuing financial institution 502 thatmay provide additional value to the issuing financial institution 502 orthe consumer 504 in the processing of payment transactions. Value-addedservices may include, for example, fraud scoring, transaction or accountcontrols, account number mapping, offer redemption, loyalty processing,etc. For instance, when the transaction processing server 512 receivesthe transaction, a fraud score for the transaction may be calculatedbased on the data included therein and one or more fraud scoringalgorithms and/or engines. In some instances, the transaction processingserver 512 may first identify the issuing financial institution 502associated with the transaction, and then identify any servicesindicated by the issuing financial institution 502 to be performed. Theissuing financial institution 502 may be identified, for example, bydata included in a specific data element included in the authorizationrequest, such as an issuer identification number. In another example,the issuing financial institution 502 may be identified by the primaryaccount number stored in the authorization request, such as by using aportion of the primary account number (e.g., a bank identificationnumber) for identification.

In step 538, the transaction processing server 512 may electronicallytransmit the authorization request to the issuing financial institution502. In some instances, the authorization request may be modified, oradditional data included in or transmitted accompanying theauthorization request as a result of the performance of value-addedservices by the transaction processing server 512. In some embodiments,the authorization request may be transmitted to a transaction processor(e.g., owned or operated by the transaction processing server 512)situated at the issuing financial institution 502 or an entityassociated thereof, which may forward the authorization request to theissuing financial institution 502.

In step 540, the issuing financial institution 502 may authorize thetransaction account for payment of the payment transaction. Theauthorization may be based on an available credit amount for thetransaction account and the transaction amount for the paymenttransaction, fraud scores provided by the transaction processing server512, and other considerations that will be apparent to persons havingskill in the relevant art. The issuing financial institution 502 maymodify the authorization request to include a response code indicatingapproval (e.g., or denial if the transaction is to be denied) of thepayment transaction. The issuing financial institution 502 may alsomodify a message type indicator for the transaction message to indicatethat the transaction message is changed to be an authorization response.In step 542, the issuing financial institution 502 may transmit (e.g.,via a transaction processor) the authorization response to thetransaction processing server 512.

In step 544, the transaction processing server 512 may forward theauthorization response to the acquiring financial institution 510 (e.g.,via a transaction processor). In step 546, the acquiring financialinstitution may generate a response message indicating approval ordenial of the payment transaction as indicated in the response code ofthe authorization response, and may transmit the response message to thegateway processor 508 using the standards and protocols set forth by thegateway processor 508. In step 548, the gateway processor 508 mayforward the response message to the merchant 506 using the appropriatestandards and protocols. In step 550, assuming the transaction wasapproved, the merchant 506 may then provide the products purchased bythe consumer 504 as part of the payment transaction to the consumer 504.

In some embodiments, once the process 500 has completed, payment fromthe issuing financial institution 502 to the acquiring financialinstitution 510 may be performed. In some instances, the payment may bemade immediately or within one business day. In other instances, thepayment may be made after a period of time, and in response to thesubmission of a clearing request from the acquiring financialinstitution 510 to the issuing financial institution 502 via thetransaction processing server 502. In such instances, clearing requestsfor multiple payment transactions may be aggregated into a singleclearing request, which may be used by the transaction processing server512 to identify overall payments to be made by whom and to whom forsettlement of payment transactions.

In some instances, the system may also be configured to perform theprocessing of payment transactions in instances where communicationpaths may be unavailable. For example, if the issuing financialinstitution is unavailable to perform authorization of the transactionaccount (e.g., in step 540), the transaction processing server 512 maybe configured to perform authorization of transactions on behalf of theissuing financial institution 502. Such actions may be referred to as“stand-in processing,” where the transaction processing server “standsin” as the issuing financial institution 502. In such instances, thetransaction processing server 512 may utilize rules set forth by theissuing financial institution 502 to determine approval or denial of thepayment transaction, and may modify the transaction message accordinglyprior to forwarding to the acquiring financial institution 510 in step544. The transaction processing server 512 may retain data associatedwith transactions for which the transaction processing server 512 standsin, and may transmit the retained data to the issuing financialinstitution 502 once communication is reestablished. The issuingfinancial institution 502 may then process transaction accountsaccordingly to accommodate for the time of lost communication.

In another example, if the transaction processing server 512 isunavailable for submission of the authorization request by the acquiringfinancial institution 510, then the transaction processor at theacquiring financial institution 510 may be configured to perform theprocessing of the transaction processing server 512 and the issuingfinancial institution 502. The transaction processor may include rulesand data suitable for use in making a determination of approval ordenial of the payment transaction based on the data included therein.For instance, the issuing financial institution 502 and/or transactionprocessing server 512 may set limits on transaction type, transactionamount, etc. that may be stored in the transaction processor and used todetermine approval or denial of a payment transaction based thereon. Insuch instances, the acquiring financial institution 510 may receive anauthorization response for the payment transaction even if thetransaction processing server 512 is unavailable, ensuring thattransactions are processed and no downtime is experienced even ininstances where communication is unavailable. In such cases, thetransaction processor may store transaction details for the paymenttransactions, which may be transmitted to the transaction processingserver 512 (e.g., and from there to the associated issuing financialinstitutions 502) once communication is reestablished.

In some embodiments, transaction processors may be configured to includea plurality of different communication channels, which may utilizemultiple communication cards and/or devices, to communicate with thetransaction processing server 512 for the sending and receiving oftransaction messages. For example, a transaction processor may becomprised of multiple computing devices, each having multiplecommunication ports that are connected to the transaction processingserver 512. In such embodiments, the transaction processor may cyclethrough the communication channels when transmitting transactionmessages to the transaction processing server 512, to alleviate networkcongestion and ensure faster, smoother communications. Furthermore, ininstances where a communication channel may be interrupted or otherwiseunavailable, alternative communication channels may thereby beavailable, to further increase the uptime of the network.

In some embodiments, transaction processors may be configured tocommunicate directly with other transaction processors. For example, atransaction processor at an acquiring financial institution 510 mayidentify that an authorization request involves an issuing financialinstitution 502 (e.g., via the bank identification number included inthe transaction message) for which no value-added services are required.The transaction processor at the acquiring financial institution 510 maythen transmit the authorization request directly to the transactionprocessor at the issuing financial institution 502 (e.g., without theauthorization request passing through the transaction processing server512), where the issuing financial institution 502 may process thetransaction accordingly.

The methods discussed above for the processing of payment transactionsthat utilize multiple methods of communication using multiplecommunication channels, and includes fail safes to provide for theprocessing of payment transactions at multiple points in the process andat multiple locations in the system, as well as redundancies to ensurethat communications arrive at their destination successfully even ininstances of interruptions, may provide for a robust system that ensuresthat payment transactions are always processed successfully with minimalerror and interruption. This advanced network and its infrastructure andtopology may be commonly referred to as “payment rails,” wheretransaction data may be submitted to the payment rails from merchants atmillions of different points of sale, to be routed through theinfrastructure to the appropriate transaction processing servers 512 forprocessing. The payment rails may be such that a general purposecomputing device may be unable to properly format or submitcommunications to the rails, without specialized programming and/orconfiguration. Through the specialized purposing of a computing device,the computing device may be configured to submit transaction data to theappropriate entity (e.g., a gateway processor 508, acquiring financialinstitution 510, etc.) for processing using this advanced network, andto quickly and efficiently receive a response regarding the ability fora consumer 504 to fund the payment transaction.

Computer System Architecture

FIG. 6 illustrates a computer system 600 in which embodiments of thepresent disclosure, or portions thereof, may be implemented ascomputer-readable code. For example, the processing server 102 of FIG. 1may be implemented in the computer system 600 using hardware, software,firmware, non-transitory computer readable media having instructionsstored thereon, or a combination thereof and may be implemented in oneor more computer systems or other processing systems. Hardware,software, or any combination thereof may embody modules and componentsused to implement the methods of FIGS. 3-5.

If programmable logic is used, such logic may execute on a commerciallyavailable processing platform configured by executable software code tobecome a specific purpose computer or a special purpose device (e.g.,programmable logic array, application-specific integrated circuit,etc.). A person having ordinary skill in the art may appreciate thatembodiments of the disclosed subject matter can be practiced withvarious computer system configurations, including multi-coremultiprocessor systems, minicomputers, mainframe computers, computerslinked or clustered with distributed functions, as well as pervasive orminiature computers that may be embedded into virtually any device. Forinstance, at least one processor device and a memory may be used toimplement the above described embodiments.

A processor unit or device as discussed herein may be a singleprocessor, a plurality of processors, or combinations thereof. Processordevices may have one or more processor “cores.” The terms “computerprogram medium,” “non-transitory computer readable medium,” and“computer usable medium” as discussed herein are used to generally referto tangible media such as a removable storage unit 618, a removablestorage unit 622, and a hard disk installed in hard disk drive 612.

Various embodiments of the present disclosure are described in terms ofthis example computer system 600. After reading this description, itwill become apparent to a person skilled in the relevant art how toimplement the present disclosure using other computer systems and/orcomputer architectures. Although operations may be described as asequential process, some of the operations may in fact be performed inparallel, concurrently, and/or in a distributed environment, and withprogram code stored locally or remotely for access by single ormulti-processor machines. In addition, in some embodiments the order ofoperations may be rearranged without departing from the spirit of thedisclosed subject matter.

Processor device 604 may be a special purpose or a general purposeprocessor device specifically configured to perform the functionsdiscussed herein. The processor device 604 may be connected to acommunications infrastructure 606, such as a bus, message queue,network, multi-core message-passing scheme, etc. The network may be anynetwork suitable for performing the functions as disclosed herein andmay include a local area network (LAN), a wide area network (WAN), awireless network (e.g., WiFi), a mobile communication network, asatellite network, the Internet, fiber optic, coaxial cable, infrared,radio frequency (RF), or any combination thereof. Other suitable networktypes and configurations will be apparent to persons having skill in therelevant art. The computer system 600 may also include a main memory 608(e.g., random access memory, read-only memory, etc.), and may alsoinclude a secondary memory 610. The secondary memory 610 may include thehard disk drive 612 and a removable storage drive 614, such as a floppydisk drive, a magnetic tape drive, an optical disk drive, a flashmemory, etc.

The removable storage drive 614 may read from and/or write to theremovable storage unit 618 in a well-known manner. The removable storageunit 618 may include a removable storage media that may be read by andwritten to by the removable storage drive 614. For example, if theremovable storage drive 614 is a floppy disk drive or universal serialbus port, the removable storage unit 618 may be a floppy disk orportable flash drive, respectively. In one embodiment, the removablestorage unit 618 may be non-transitory computer readable recordingmedia.

In some embodiments, the secondary memory 610 may include alternativemeans for allowing computer programs or other instructions to be loadedinto the computer system 600, for example, the removable storage unit622 and an interface 620. Examples of such means may include a programcartridge and cartridge interface (e.g., as found in video gamesystems), a removable memory chip (e.g., EEPROM, PROM, etc.) andassociated socket, and other removable storage units 622 and interfaces620 as will be apparent to persons having skill in the relevant art.

Data stored in the computer system 600 (e.g., in the main memory 608and/or the secondary memory 610) may be stored on any type of suitablecomputer readable media, such as optical storage (e.g., a compact disc,digital versatile disc, Blu-ray disc, etc.) or magnetic tape storage(e.g., a hard disk drive). The data may be configured in any type ofsuitable database configuration, such as a relational database, astructured query language (SQL) database, a distributed database, anobject database, etc. Suitable configurations and storage types will beapparent to persons having skill in the relevant art.

The computer system 600 may also include a communications interface 624.The communications interface 624 may be configured to allow software anddata to be transferred between the computer system 600 and externaldevices. Exemplary communications interfaces 624 may include a modem, anetwork interface (e.g., an Ethernet card), a communications port, aPCMCIA slot and card, etc. Software and data transferred via thecommunications interface 624 may be in the form of signals, which may beelectronic, electromagnetic, optical, or other signals as will beapparent to persons having skill in the relevant art. The signals maytravel via a communications path 626, which may be configured to carrythe signals and may be implemented using wire, cable, fiber optics, aphone line, a cellular phone link, a radio frequency link, etc.

The computer system 600 may further include a display interface 602. Thedisplay interface 602 may be configured to allow data to be transferredbetween the computer system 600 and external display 630. Exemplarydisplay interfaces 602 may include high-definition multimedia interface(HDMI), digital visual interface (DVI), video graphics array (VGA), etc.The display 630 may be any suitable type of display for displaying datatransmitted via the display interface 602 of the computer system 600,including a cathode ray tube (CRT) display, liquid crystal display(LCD), light-emitting diode (LED) display, capacitive touch display,thin-film transistor (TFT) display, etc.

Computer program medium and computer usable medium may refer tomemories, such as the main memory 608 and secondary memory 610, whichmay be memory semiconductors (e.g., DRAMs, etc.). These computer programproducts may be means for providing software to the computer system 600.Computer programs (e.g., computer control logic) may be stored in themain memory 608 and/or the secondary memory 610. Computer programs mayalso be received via the communications interface 624. Such computerprograms, when executed, may enable computer system 600 to implement thepresent methods as discussed herein. In particular, the computerprograms, when executed, may enable processor device 604 to implementthe methods illustrated by FIGS. 3-5, as discussed herein. Accordingly,such computer programs may represent controllers of the computer system600. Where the present disclosure is implemented using software, thesoftware may be stored in a computer program product and loaded into thecomputer system 600 using the removable storage drive 614, interface620, and hard disk drive 612, or communications interface 624.

The processor device 604 may comprise one or more modules or enginesconfigured to perform the functions of the computer system 600. Each ofthe modules or engines may be implemented using hardware and, in someinstances, may also utilize software, such as corresponding to programcode and/or programs stored in the main memory 608 or secondary memory610. In such instances, program code may be compiled by the processordevice 604 (e.g., by a compiling module or engine) prior to execution bythe hardware of the computer system 600. For example, the program codemay be source code written in a programming language that is translatedinto a lower level language, such as assembly language or machine code,for execution by the processor device 604 and/or any additional hardwarecomponents of the computer system 600. The process of compiling mayinclude the use of lexical analysis, preprocessing, parsing, semanticanalysis, syntax-directed translation, code generation, codeoptimization, and any other techniques that may be suitable fortranslation of program code into a lower level language suitable forcontrolling the computer system 600 to perform the functions disclosedherein. It will be apparent to persons having skill in the relevant artthat such processes result in the computer system 600 being a speciallyconfigured computer system 600 uniquely programmed to perform thefunctions discussed above.

Techniques consistent with the present disclosure provide, among otherfeatures, systems and methods for real-time measurement of campaigneffectiveness. While various exemplary embodiments of the disclosedsystem and method have been described above it should be understood thatthey have been presented for purposes of example only, not limitations.It is not exhaustive and does not limit the disclosure to the preciseform disclosed. Modifications and variations are possible in light ofthe above teachings or may be acquired from practicing of thedisclosure, without departing from the breadth or scope.

What is claimed is:
 1. A method for real-time measurement of campaigneffectiveness, comprising: storing, in a device database of a processingserver, a plurality of device profiles, wherein each device profileincludes a structured data set related to a computing device includingat least a hashed device identifier, an associated geographic location,and a plurality of transaction data entries, each transaction data entryincluding data related to a payment transaction including at least, anaccount identifier, a transaction date, and transaction data; receiving,by a receiving device of the processing server, a data signalsuperimposed with a data file from a computing system, wherein the datafile includes data related to a current campaign including at least, astart date, an end date, at least one merchant identifier, and aplurality of first device identifiers involved in the current campaign,and, for each first device identifier, a category identifier of a set ofcategory identifiers to which a respective first device identifier isapplied; generating, by a hashing module of the processing server, ahashed identifier for each of the plurality of first device identifiersincluded via application of a hashing algorithm to the respective firstdevice identifier; executing, by a querying module of the processingserver, a query on the device database to identify, for each of theplurality of first device identifiers, a corresponding device profilewhere the included hashed device identifier corresponds to the hashedidentifier generated for the respective first device identifier;calculating, by a calculation module of the processing server, at leastone purchase behavior for each category identifier of the set ofcategory identifiers for each of the at least one merchant identifiers,each category identifier defining at least: one or more groupsassociated with the first device identifiers and second deviceidentifiers; and whether each of the one or more groups is exposed tothe current campaign, the at least one purchase behavior including atleast one or more of: average transaction spend, transaction frequency,and number of transactions, wherein each purchase behavior is based onat least: first transaction data obtained from one or more firsttransaction data entries associated with one or more computing devicesincluded in the plurality of device profiles, the one or more firsttransaction data entries include an account identifier of a respectivefirst device profile and a first transaction date between the start dateand end date of the current campaign included in each correspondingdevice profile identified for device identifiers of the plurality offirst device identifiers where the first device identifier is associatedwith the respective category identifier, and the account identifierassociated with a respective device profile, and where the correspondingdevice profile includes an associated geographic location correspondingto the respective merchant identifier; second transaction data obtainedfrom one or more second transaction data entries associated with one ormore payment devices not included in the plurality of device profiles,the one or more second transaction data entries including the accountidentifier of a respective second device profile and a secondtransaction date between the start date and end date of the currentcampaign included in each corresponding device profile identified fordevice identifiers of the plurality of first device identifiers, and theone or more second transaction data entries also include the accountidentifier of the respective second device profile; and thirdtransaction data obtained from one or more third transaction dataentries associated with the one or more payment devices not included inthe plurality of device profiles, the one or more third transaction dataentries including a third transaction date between the start date andend date of the current campaign, which are included in eachcorresponding device profile identified for device identifiers of aplurality of second device identifiers; and electronically transmitting,by a transmitting device of the processing server, a data signalsuperimposed with a response data file associated with the currentcampaign to the computing system, wherein the response data fileincludes: the at least one purchase behavior calculated for eachcategory identifier for each of the at least one merchant identifiers,and one or more metrics based on the at least one purchase behaviorcalculated for each category identifier for each of the at least onemerchant identifiers, at least one of the one or more metrics being avalue which rates industry growth for a specified category identifierbased on purchase behavior of the first device identifiers generatingthe first transaction data and purchase behavior of the one or morepayment devices not included in the plurality of device profiles ascompared to purchase behavior of the second device identifiersgenerating the third transaction data, the data signal superimposed withthe response data file being formatted according to a standard specifiedby the computing system for initiating one or more actions in thecomputing system, wherein the transmitting device selects one of aplurality of different communication channels based on one or more ofavailability and congestion for transmitting the data signalsuperimposed with the response data.
 2. The method of claim 1, furthercomprising: calculating, by the calculation module of the processingserver, a campaign effectiveness value for the campaign based on acomparison, for each of the at least one merchant identifier, of the atleast one purchase behavior calculated for each category identifier forthe respective at least one merchant identifier, the comparisonproducing at least one value representative of one or more differencesbetween the set of category identifiers, wherein the one or more metricsincludes the calculated campaign effectiveness value.
 3. The method ofclaim 2, wherein the set of category identifiers includes a test groupidentifier and a control group identifier.
 4. The method of claim 1,wherein each of the at least one merchant identifiers is a geographiclocation associated with one or more merchants.
 5. The method of claim1, further comprising: storing, in a merchant database of the processingserver, a plurality of merchant profiles, wherein each merchant profileincludes a structured data set related to a merchant including at leastthe merchant identifier and a merchant geographic location; andexecuting, by the querying module of the processing server, a query onthe merchant database to identify, for each of the at least one merchantidentifier, a corresponding merchant profile that includes therespective merchant identifier, wherein the correspondence between theassociated geographic location included in a device profile and amerchant identifier is based on a correspondence between the associatedgeographic location and the merchant geographic location included in themerchant profile corresponding to the respective merchant identifier. 6.The method of claim 5, wherein the merchant identifier is one of: amerchant identification number and a merchant name.
 7. The method ofclaim 1, wherein the one or more metrics includes at least one of:change in average spend, change in total spend, change in transactionfrequency, and change in number of transactions.
 8. The method of claim1, wherein each device profile further includes one or more demographiccharacteristics of a set of demographic characteristics, the at leastone purchase behavior calculated for each category identifier of the setof category identifiers for each of the at least one merchantidentifiers are calculated for each demographic characteristic of theset of demographic characteristics, and the at least one purchasebehavior is based on the first transaction data and the secondtransaction data, wherein the included one or more demographiccharacteristics include the respective demographic characteristic. 9.The method of claim 8, wherein the data file further includes the set ofdemographic characteristics.
 10. The method of claim 8, furthercomprising: calculating, by the calculation module of the processingserver for each of the at least one merchant identifier and demographiccharacteristic, a campaign effectiveness value for the campaign based ona comparison of a plurality of purchase behaviors, wherein each purchasebehavior is calculated for each category identifier for the respectiveat least one merchant identifier and demographic characteristic, thecomparison producing at least one value representative of one or moredifferences between the set of category identifiers, wherein the one ormore metrics includes the calculated campaign effectiveness value.
 11. Asystem for real-time measurement of campaign effectiveness, comprising:a device database of a processing server stores a plurality of deviceprofiles, wherein each device profile includes a structured data setrelated to a computing device including at least a hashed deviceidentifier, an associated geographic location, and a plurality oftransaction data entries, each transaction data entry including datarelated to a payment transaction including at least an accountidentifier, a transaction date, and transaction data; a receiving deviceof the processing server receives a data signal superimposed with a datafile from a computing system, wherein the data file includes datarelated to a current campaign including at least, a start date, an enddate, at least one merchant identifier, and a plurality of first deviceidentifiers involved in the current campaign, and, for each first deviceidentifier, a category identifier of a set of category identifiers towhich a respective first device identifier is applied; a hashing moduleof the processing server generates a hashed identifier for each of theplurality of first device identifiers included via application of ahashing algorithm to the respective first device identifier; a queryingmodule of the processing server executes a query on the device databaseto identify, for each of the plurality of first device identifiers, acorresponding device profile where the included hashed device identifiercorresponds to the hashed identifier generated for the respective firstdevice identifier; a calculation module of the processing servercalculates at least one purchase behavior to determine one or more of anaverage transaction spend, transaction frequency, and number oftransactions, the purchase behavior being calculated for each categoryidentifier of the set of category identifiers for each of the at leastone merchant identifiers, each category identifier defining at least:one or more groups associated with the first device identifiers andsecond device identifiers; and whether each of the one or more groups isexposed to the current campaign, wherein each purchase behavior is basedon at least: first transaction data obtained from one or more firsttransaction data entries associated with one or more computing devicesincluded in the plurality of device profiles, the one or more firsttransaction data entries include an account identifier of a respectivedevice profile and a first transaction date between the start date andend date of the current campaign included in each corresponding deviceprofile identified for device identifiers of the plurality of firstdevice identifiers where the device identifier is associated with therespective category identifier, and the account identifier associatedwith a respective device profile, and where the corresponding deviceprofile includes an associated geographic location corresponding to therespective merchant identifier; and second transaction data obtainedfrom one or more second transaction data entries associated with one ormore payment devices not included in the plurality of device profiles,the one or more second transaction data entries including the accountidentifier of a respective second device profile and a secondtransaction date between the start date and end date of the currentcampaign included in each corresponding device profile identified fordevice identifiers of the plurality of first device identifiers, and theone or more second transaction data entries also include the accountidentifier of the respective second device profile; and thirdtransaction data obtained from one or more third transaction dataentries associated with the one or more payment devices not included inthe plurality of device profiles, the one or more third transaction dataentries including a third transaction date between the start date andend date of the current campaign, which are included in eachcorresponding device profile identified for device identifiers of aplurality of second device identifiers; and a transmitting device of theprocessing server electronically transmits a data signal superimposedwith a response data file associated with the current campaign to thecomputing system, wherein the response data file includes: the at leastone purchase behavior calculated for each category identifier for eachof the at least one merchant identifiers, and one or more metrics basedon the at least one purchase behavior calculated for each categoryidentifier for each of the at least one merchant identifiers, at leastone of the one or more metrics being a value which rates industry growthfor a specified category identifier based on purchase behavior of thefirst device identifiers generating the first transaction data andpurchase behavior of the one or more payment devices not included in theplurality of device profiles as compared to purchase behavior of thesecond device identifiers generating the third transaction data, thedata signal superimposed with the response data file being formattedaccording to a standard specified by the computing system for initiatingone or more actions in the computing system, wherein the transmittingdevice is configured to electronically transmit by the data signalsuperimposed with the response data by selecting one of a plurality ofdifferent communication channels based on one or more of availabilityand congestion for transmitting.
 12. The system of claim 11, wherein thecalculation module of the processing server calculates, for each of theat least one merchant identifier, a campaign effectiveness value for thecampaign based on a comparison of the at least one purchase behaviorcalculated for each category identifier for the respective at least onemerchant identifier, the comparison producing at least one valuerepresentative of one or more differences between the set of categoryidentifiers, and the one or more metrics includes the calculatedcampaign effectiveness value.
 13. The system of claim 12, wherein theset of category identifiers includes a test group identifier and acontrol group identifier.
 14. The system of claim 11, wherein each ofthe at least one merchant identifiers is a geographic locationassociated with one or more merchants.
 15. The system of claim 11,further comprising: a merchant database of the processing server storesa plurality of merchant profiles, wherein each merchant profile includesa structured data set related to a merchant including at least themerchant identifier and a merchant geographic location, wherein thequerying module of the processing server executes a query on themerchant database to identify, for each of the at least one merchantidentifier, a corresponding merchant profile that includes therespective merchant identifier, and the correspondence between theassociated geographic location included in a device profile and amerchant identifier is based on a correspondence between the associatedgeographic location and the merchant geographic location included in themerchant profile corresponding to the respective merchant identifier.16. The system of claim 15, wherein the merchant identifier is one of: amerchant identification number and a merchant name.
 17. The system ofclaim 11, wherein the one or more metrics includes at least one of:change in average spend, change in total spend, change in transactionfrequency, and change in number of transactions.
 18. The system of claim11, wherein each device profile further includes one or more demographiccharacteristics of a set of demographic characteristics, the at leastone purchase behavior calculated for each category identifier of the setof category identifiers for each of the at least one merchantidentifiers are calculated for each demographic characteristic of theset of demographic characteristics, and the at least one purchasebehavior is based on the first transaction data and the secondtransaction data, wherein the included one or more demographiccharacteristics include the respective demographic characteristic. 19.The system of claim 18, wherein the data file further includes the setof demographic characteristics.
 20. The system of claim 18, wherein thecalculation module of the processing server calculates a campaigneffectiveness value for the campaign based on a comparison, for each ofthe at least one merchant identifier and demographic characteristic, ofa plurality of purchase behaviors, wherein each purchase behavior iscalculated for each category identifier for the respective at least onemerchant identifier and demographic characteristic, and the one or moremetrics includes the calculated campaign effectiveness value.